IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v293y2024ics0360544224003918.html
   My bibliography  Save this article

Reduction of electricity consumption in an AHU using mathematical modelling for controller tuning

Author

Listed:
  • García Vázquez, C.A.
  • Cotfas, D.T.
  • González Santos, A.I.
  • Cotfas, P.A.
  • León Ávila, B.Y.

Abstract

Energy consumed by HVAC (heating, ventilating and air conditioning) systems represents a considerable part of the energy consumed in buildings. This paper focuses on achieving energy efficiency, through automatic control strategies, of HVAC systems in the biopharmaceutical industry, a sector little covered by previous studies, mainly focused on residential and commercial buildings. The system under study is an air handling unit (AHU). The main contributions of this research are the obtaining of a dynamic, multivariable, and non-linear model of the AHU, proposing a relatively simple structure and the procedure to estimate its parameters; a non-linear static model of the power consumption of its bank of electrical resistors, also simple, but useful to guide the PID tuning toward energy efficiency; and the approximation to the model of a PID controller whose control low is unknown. The methods proposed to obtain the models and to perform the simulations are also provided. Results for a close-to-reality simulation scenario that suggests the possibility of reducing the power consumed by the resistor bank by 29 % are presented. The use of an industrial PI control algorithm, instead of the classical textbook algorithm, also distinguishes this work from others.

Suggested Citation

  • García Vázquez, C.A. & Cotfas, D.T. & González Santos, A.I. & Cotfas, P.A. & León Ávila, B.Y., 2024. "Reduction of electricity consumption in an AHU using mathematical modelling for controller tuning," Energy, Elsevier, vol. 293(C).
    • Handle: RePEc:eee:energy:v:293:y:2024:i:c:s0360544224003918
    DOI: 10.1016/j.energy.2024.130619
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224003918
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.130619?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xiaowu Li & Kun Sun & Hongbo Fan & Zihan He, 2023. "Real-Time Cattle Pose Estimation Based on Improved RTMPose," Agriculture, MDPI, vol. 13(10), pages 1-18, October.
    2. Jonathan Roth & Pedro H. C. Sant’Anna, 2023. "Efficient Estimation for Staggered Rollout Designs," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 1(4), pages 669-709.
    3. Song, Kwonsik & Jang, Youjin & Park, Moonseo & Lee, Hyun-Soo & Ahn, Joseph, 2020. "Energy efficiency of end-user groups for personalized HVAC control in multi-zone buildings," Energy, Elsevier, vol. 206(C).
    4. Wen, Shuqing & Zhang, Weirong & Sun, Yifu & Li, Zhenxi & Huang, Boju & Bian, Shouguo & Zhao, Lin & Wang, Yan, 2023. "An enhanced principal component analysis method with Savitzky–Golay filter and clustering algorithm for sensor fault detection and diagnosis," Applied Energy, Elsevier, vol. 337(C).
    5. Yukun Ma & Pedro H. C. Sant'Anna & Yuya Sasaki & Takuya Ura, 2023. "Doubly Robust Estimators with Weak Overlap," Papers 2304.08974, arXiv.org, revised Apr 2023.
    6. Salins, Sampath Suranjan & Kumar, Sreejith Sanal & Thommana, Antony John Jose & Vincent, Vivian Christo & Tejero-González, Ana & Kumar, Shiva, 2023. "Performance characterization of an adaptive-controlled air handling unit to achieve thermal comfort in Dubai climate," Energy, Elsevier, vol. 273(C).
    7. Homod, Raad Z. & Gaeid, Khalaf S. & Dawood, Suroor M. & Hatami, Alireza & Sahari, Khairul S., 2020. "Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings," Applied Energy, Elsevier, vol. 271(C).
    8. Guanjing Lin & Armando Casillas & Maggie Sheng & Jessica Granderson, 2023. "Performance Evaluation of an Occupancy-Based HVAC Control System in an Office Building," Energies, MDPI, vol. 16(20), pages 1-21, October.
    9. Adrian Chojecki & Arkadiusz Ambroziak & Piotr Borkowski, 2023. "Fuzzy Controllers Instead of Classical PIDs in HVAC Equipment: Dusting Off a Well-Known Technology and Today’s Implementation for Better Energy Efficiency and User Comfort," Energies, MDPI, vol. 16(7), pages 1-21, March.
    10. Tillmann, Andreas M. & Joormann, Imke & Ammann, Sabrina C.L., 2023. "Reproducible air passenger demand estimation," Journal of Air Transport Management, Elsevier, vol. 112(C).
    11. Khan, Muhammad Waqas & Choudhry, Mohammad Ahmad & Zeeshan, Muhammad & Ali, Ahsan, 2015. "Adaptive fuzzy multivariable controller design based on genetic algorithm for an air handling unit," Energy, Elsevier, vol. 81(C), pages 477-488.
    12. Li, Xiaoting & Joe, Harry, 2023. "Estimation of multivariate tail quantities," Computational Statistics & Data Analysis, Elsevier, vol. 185(C).
    13. Shaomin Li & Kangning Wang & Yong Xu, 2023. "Robust estimation for nonrandomly distributed data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 493-509, June.
    14. Wenjuan Li & Wenying Wang & Jingsi Chen & Weidong Rao, 2023. "Aggregate Kernel Inverse Regression Estimation," Mathematics, MDPI, vol. 11(12), pages 1-10, June.
    15. Fang, Xi & Gong, Guangcai & Li, Guannan & Chun, Liang & Peng, Pei & Li, Wenqiang & Shi, Xing, 2023. "Cross temporal-spatial transferability investigation of deep reinforcement learning control strategy in the building HVAC system level," Energy, Elsevier, vol. 263(PB).
    16. Mawson, Victoria Jayne & Hughes, Ben Richard, 2020. "Thermal modelling of manufacturing processes and HVAC systems," Energy, Elsevier, vol. 204(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cui, Can & Xue, Jing, 2024. "Energy and comfort aware operation of multi-zone HVAC system through preference-inspired deep reinforcement learning," Energy, Elsevier, vol. 292(C).
    2. Waseem, Muhammad & Lin, Zhenzhi & Liu, Shengyuan & Zhang, Zhi & Aziz, Tarique & Khan, Danish, 2021. "Fuzzy compromised solution-based novel home appliances scheduling and demand response with optimal dispatch of distributed energy resources," Applied Energy, Elsevier, vol. 290(C).
    3. Esmaeilzadeh, Ahmad & Deal, Brian & Yousefi-Koma, Aghil & Zakerzadeh, Mohammad Reza, 2023. "How combination of control methods and renewable energies leads a large commercial building to a zero-emission zone – A case study in U.S," Energy, Elsevier, vol. 263(PD).
    4. Sun, Hongchang & Niu, Yanlei & Li, Chengdong & Zhou, Changgeng & Zhai, Wenwen & Chen, Zhe & Wu, Hao & Niu, Lanqiang, 2022. "Energy consumption optimization of building air conditioning system via combining the parallel temporal convolutional neural network and adaptive opposition-learning chimp algorithm," Energy, Elsevier, vol. 259(C).
    5. Lee, Minjung & Ham, Jeonggyun & Lee, Jeong-Won & Cho, Honghyun, 2023. "Analysis of thermal comfort, energy consumption, and CO2 reduction of indoor space according to the type of local heating under winter rest conditions," Energy, Elsevier, vol. 268(C).
    6. Carattini, Stefano & Figge, Béla & Gordan, Alexander & Löschel, Andreas, 2024. "Municipal building codes and the adoption of solar photovoltaics," Journal of Environmental Economics and Management, Elsevier, vol. 124(C).
    7. Sun, Chunhua & Zhang, Haixiang & Cao, Shanshan & Xia, Guoqiang & Zhong, Jian & Wu, Xiangdong, 2023. "A hierarchical classifying and two-step training strategy for detection and diagnosis of anormal temperature in district heating system," Applied Energy, Elsevier, vol. 349(C).
    8. He, Xianya & Huang, Jingzhi & Liu, Zekun & Lin, Jian & Jing, Rui & Zhao, Yingru, 2023. "Topology optimization of thermally activated building system in high-rise building," Energy, Elsevier, vol. 284(C).
    9. Hamid Ahaggach & Lylia Abrouk & Eric Lebon, 2024. "Systematic Mapping Study of Sales Forecasting: Methods, Trends, and Future Directions," Forecasting, MDPI, vol. 6(3), pages 1-31, July.
    10. He, Fuli & Yarahmadi, Ali & Soleymani, Fazlollah, 2024. "Investigation of multivariate pairs trading under copula approach with mixture distribution," Applied Mathematics and Computation, Elsevier, vol. 472(C).
    11. Dmitry Arkhangelsky & Guido W. Imbens & Lihua Lei & Xiaoman Luo, 2021. "Design-Robust Two-Way-Fixed-Effects Regression For Panel Data," Papers 2107.13737, arXiv.org, revised Mar 2024.
    12. Hua, Pengmin & Wang, Haichao & Xie, Zichan & Lahdelma, Risto, 2024. "Multi-criteria evaluation of novel multi-objective model predictive control method for indoor thermal comfort," Energy, Elsevier, vol. 289(C).
    13. Yang Liu & Xin Wang & Guilin Xie & Congcong Zhao, 2023. "Study on the Relationship between Indoor Vertical Greening and Oxygen Content in High-Rise Buildings," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    14. Krzysztof Lalik & Mateusz Kozek & Szymon Podlasek & Rafał Figaj & Paweł Gut, 2021. "Q-Learning Neural Controller for Steam Generator Station in Micro Cogeneration Systems," Energies, MDPI, vol. 14(17), pages 1-13, August.
    15. Halhoul Merabet, Ghezlane & Essaaidi, Mohamed & Ben Haddou, Mohamed & Qolomany, Basheer & Qadir, Junaid & Anan, Muhammad & Al-Fuqaha, Ala & Abid, Mohamed Riduan & Benhaddou, Driss, 2021. "Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    16. Fan, Cheng & Wu, Qiuting & Zhao, Yang & Mo, Like, 2024. "Integrating active learning and semi-supervised learning for improved data-driven HVAC fault diagnosis performance," Applied Energy, Elsevier, vol. 356(C).
    17. Humberto Verdejo & Rodrigo Torres & Victor Pino & Wolfgang Kliemann & Cristhian Becker & José Delpiano, 2019. "Tuning of Controllers in Power Systems Using a Heuristic-Stochastic Approach," Energies, MDPI, vol. 12(12), pages 1-25, June.
    18. Amal Azzi & Mohamed Tabaa & Badr Chegari & Hanaa Hachimi, 2024. "Balancing Sustainability and Comfort: A Holistic Study of Building Control Strategies That Meet the Global Standards for Efficiency and Thermal Comfort," Sustainability, MDPI, vol. 16(5), pages 1-36, March.
    19. Clément de Chaisemartin & Xavier D’Haultfœuille, 2023. "Two-way fixed effects and differences-in-differences with heterogeneous treatment effects: a survey," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 1-30.
    20. Gregory Gilpin & Ezra Karger & Peter Nencka, 2024. "The Returns to Public Library Investment," American Economic Journal: Economic Policy, American Economic Association, vol. 16(2), pages 78-109, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:293:y:2024:i:c:s0360544224003918. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.